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Parallel multitarget tracking particle filters using Graphics Processing Unit

机译:使用图形处理单元的并行多目标跟踪粒子滤波器

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This paper presents design, implementation, and performance evaluation results of parallel multitarget tracking particle filters using a Graphics Processing Unit (GPU) as a parallel computing environment. Since the resampling step is a bottleneck in parallel particle filtering two parallel tracking algorithms are implemented and compared - with centralized resampling and with distributed resampling using proportional allocation, respectively. Performance evaluation and comparison between both parallel implementations, and with a fully centralized implementation are provided based on experimental data obtained from several simulated multitarget tracking scenarios.
机译:本文介绍了使用图形处理单元(GPU)作为并行计算环境的并行多目标跟踪粒子滤波器的设计,实现和性能评估结果。由于重采样步骤是并行粒子滤波的瓶颈,因此实施并比较了两种并行跟踪算法-分别是集中式重采样和使用比例分配的分布式重采样。基于从几种模拟的多目标跟踪方案获得的实验数据,提供了两种并行实现之间以及完全集中的实现之间的性能评估和比较。

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